Título:
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Data science applied to refining socio-economic indicators for decision-making
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Autores:
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Salcedo Galiano, Antonio Maurilio
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Tipo de documento:
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texto impreso
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Editorial:
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Universidad Complutense de Madrid, 2019-09-11
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Dimensiones:
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application/pdf
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Nota general:
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info:eu-repo/semantics/openAccess
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Idiomas:
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Palabras clave:
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Estado = No publicado
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Materia = Ciencias: Informática: Bases de datos
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Materia = Ciencias: Estadística: Técnicas de Investigación Social
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Materia = Ciencias: Estadística: Muestreo (Estadística)
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Materia = Ciencias: Estadística: Control Estadístico de la Calidad
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Materia = Ciencias Sociales: Sociología: Estadísticas e indicadores sociales
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Materia = Ciencias Sociales: Sociología: Investigación social
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Tipo = Tesis
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Resumen:
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The construction of socio-economic well-being indicators to represent reality in the most accurate way constitutes an important challenge in the production of statistics, as recognized by prestigious international organizations. The production of different harmonized surveys in the last years allows us to have enough empirical data that offer an interesting opportunity to try to refine, if possible, the existing classic models of indicators compilation. Putting the attention on one of the aspect with greater degree of complexity - its current paradigm of objective measurement of poverty - the main elements and
approaches are analysed and the following three specific issues are addressed: Equivalization, Thresholds, Multidimensional approach...
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En línea:
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https://eprints.ucm.es/id/eprint/59563/1/T41853.pdf
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